In today's fast-paced financial markets, investors need to access information quickly and easily in order to process trading decisions. With the significant growth of online trading, individual investors need effective market analysis tools to help them make better trading decisions. Because the saying “a picture is worth a thousand words” still holds true, traders all over the world rely on traditional bar charts to display both past and present price activity. Bar charts are valuable because they reflect the history of price movement in an easy to process format (a picture.) An investor can literally analyze a chart in a glance. Although bar charts have proven to be valuable tools in the investment field, a frequently asked question is “are traditional bar (price) charts alone the most effective way define relative overbought price levels, relative oversold price levels, or fair value?” As will be shown, price can be displayed in a format which makes is possible to define the relative valuation of any market.
With the advancement in personal computers, the Internet, and online trading, trading in the stock (bonds, and futures) market has significantly increased in popularity. Investors have significant resources to utilize when determining what stock to buy or sell. However, until now, investors have not had a powerful charting tool that can quantify relative value and identify optimal market entry or exit price levels. A market analysis tool that can identify relative overbought and oversold price levels will potentially allow investors to lower their risk exposure (to loss) by helping buyers to enter markets at relatively oversold (undervalued) price levels and sellers to exit markets at relatively overbought (overvalued) price levels. Thus, buying at lower price levels and selling at higher price levels a trader is able to enhance his or her profit potential.
Furthermore, with the recent advancements in computers, many traders are now developing automated and/or mathematical computerized trading systems. These trading systems rely on quantifiable price levels to generate buy and sell signals. Until now, the most common quantifiable price levels used to drive trading systems have been the opening or closing price of a time period (day, week, month, 10-minute bar, etc.). The previous day's (or time period's) highs and lows have also been used as quantifiable reference price levels to direct trading systems to enter or exit markets. Any method or market analysis technique that could expand the number of quantifiable price or value levels to drive automated or mathematical trading systems would be extremely useful to traders, trading services and/or trading system designers.